CLN: add typing to dtype arg in core/internals, core/reshape and core (GH38808) (#39030)

Author: avinashpancham

pandas/core/base.py

@@ -19,7 +19,7 @@
 import numpy as np
 
 import pandas._libs.lib as lib
-from pandas._typing import DtypeObj, IndexLabel
+from pandas._typing import Dtype, DtypeObj, IndexLabel
 from pandas.compat import PYPY
 from pandas.compat.numpy import function as nv
 from pandas.errors import AbstractMethodError
@@ -500,7 +500,13 @@ def array(self) -> ExtensionArray:
  """
  raise AbstractMethodError(self)
 
- def to_numpy(self, dtype=None, copy=False, na_value=lib.no_default, **kwargs):
+ def to_numpy(
+ self,
+ dtype: Optional[Dtype] = None,
+ copy: bool = False,
+ na_value=lib.no_default,
+ **kwargs,
+ ):
  """
  A NumPy ndarray representing the values in this Series or Index.
 

pandas/core/generic.py

@@ -37,13 +37,16 @@
 from pandas._typing import (
  Axis,
  CompressionOptions,
+ Dtype,
+ DtypeArg,
  FilePathOrBuffer,
  FrameOrSeries,
  IndexKeyFunc,
  IndexLabel,
  JSONSerializable,
  Label,
  Level,
+ NpDtype,
  Renamer,
  StorageOptions,
  TimedeltaConvertibleTypes,
@@ -210,7 +213,9 @@ def __init__(
  object.__setattr__(self, "_flags", Flags(self, allows_duplicate_labels=True))
 
  @classmethod
- def _init_mgr(cls, mgr, axes, dtype=None, copy: bool = False) -> BlockManager:
+ def _init_mgr(
+ cls, mgr, axes, dtype: Optional[Dtype] = None, copy: bool = False
+ ) -> BlockManager:
  """ passed a manager and a axes dict """
  for a, axe in axes.items():
  if axe is not None:
@@ -1901,7 +1906,7 @@ def empty(self) -> bool_t:
  # GH#23114 Ensure ndarray.__op__(DataFrame) returns NotImplemented
  __array_priority__ = 1000
 
- def __array__(self, dtype=None) -> np.ndarray:
+ def __array__(self, dtype: Optional[NpDtype] = None) -> np.ndarray:
  return np.asarray(self._values, dtype=dtype)
 
  def __array_wrap__(
@@ -2642,7 +2647,7 @@ def to_sql(
  index: bool_t = True,
  index_label=None,
  chunksize=None,
- dtype=None,
+ dtype: Optional[DtypeArg] = None,
  method=None,
  ) -> None:
  """

pandas/core/internals/blocks.py

@@ -15,7 +15,7 @@
 )
 from pandas._libs.internals import BlockPlacement
 from pandas._libs.tslibs import conversion
-from pandas._typing import ArrayLike, DtypeObj, Scalar, Shape
+from pandas._typing import ArrayLike, Dtype, DtypeObj, Scalar, Shape
 from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core.dtypes.cast import (
@@ -241,7 +241,7 @@ def array_values(self) -> ExtensionArray:
  """
  return PandasArray(self.values)
 
- def get_values(self, dtype=None):
+ def get_values(self, dtype: Optional[Dtype] = None):
  """
  return an internal format, currently just the ndarray
  this is often overridden to handle to_dense like operations
@@ -1669,7 +1669,7 @@ def setitem(self, indexer, value):
  self.values[indexer] = value
  return self
 
- def get_values(self, dtype=None):
+ def get_values(self, dtype: Optional[Dtype] = None):
  # ExtensionArrays must be iterable, so this works.
  # TODO(EA2D): reshape not needed with 2D EAs
  return np.asarray(self.values).reshape(self.shape)
@@ -1990,7 +1990,7 @@ class DatetimeLikeBlockMixin(Block):
 
  _can_hold_na = True
 
- def get_values(self, dtype=None):
+ def get_values(self, dtype: Optional[Dtype] = None):
  """
  return object dtype as boxed values, such as Timestamps/Timedelta
  """
@@ -2168,7 +2168,7 @@ def is_view(self) -> bool:
  # check the ndarray values of the DatetimeIndex values
  return self.values._data.base is not None
 
- def get_values(self, dtype=None):
+ def get_values(self, dtype: Optional[Dtype] = None):
  """
  Returns an ndarray of values.
 
@@ -2449,7 +2449,7 @@ def replace(
 # Constructor Helpers
 
 
-def get_block_type(values, dtype=None):
+def get_block_type(values, dtype: Optional[Dtype] = None):
  """
  Find the appropriate Block subclass to use for the given values and dtype.
 
@@ -2464,7 +2464,7 @@ def get_block_type(values, dtype=None):
  """
  # We use vtype and kind checks because they are much more performant
  # than is_foo_dtype
- dtype = dtype or values.dtype
+ dtype = cast(np.dtype, pandas_dtype(dtype) if dtype else values.dtype)
  vtype = dtype.type
  kind = dtype.kind
 
@@ -2500,7 +2500,7 @@ def get_block_type(values, dtype=None):
  return cls
 
 
-def make_block(values, placement, klass=None, ndim=None, dtype=None):
+def make_block(values, placement, klass=None, ndim=None, dtype: Optional[Dtype] = None):
  # Ensure that we don't allow PandasArray / PandasDtype in internals.
  # For now, blocks should be backed by ndarrays when possible.
  if isinstance(values, ABCPandasArray):

pandas/core/internals/managers.py

@@ -17,7 +17,7 @@
 import numpy as np
 
 from pandas._libs import internals as libinternals, lib
-from pandas._typing import ArrayLike, DtypeObj, Label, Shape
+from pandas._typing import ArrayLike, Dtype, DtypeObj, Label, Shape
 from pandas.errors import PerformanceWarning
 from pandas.util._validators import validate_bool_kwarg
 
@@ -816,7 +816,7 @@ def copy_func(ax):
  def as_array(
  self,
  transpose: bool = False,
- dtype=None,
+ dtype: Optional[Dtype] = None,
  copy: bool = False,
  na_value=lib.no_default,
  ) -> np.ndarray:
@@ -872,7 +872,9 @@ def as_array(
 
  return arr.transpose() if transpose else arr
 
- def _interleave(self, dtype=None, na_value=lib.no_default) -> np.ndarray:
+ def _interleave(
+ self, dtype: Optional[Dtype] = None, na_value=lib.no_default
+ ) -> np.ndarray:
  """
  Return ndarray from blocks with specified item order
  Items must be contained in the blocks
@@ -1842,7 +1844,7 @@ def _simple_blockify(tuples, dtype) -> List[Block]:
  return [block]
 
 
-def _multi_blockify(tuples, dtype=None):
+def _multi_blockify(tuples, dtype: Optional[Dtype] = None):
  """ return an array of blocks that potentially have different dtypes """
  # group by dtype
  grouper = itertools.groupby(tuples, lambda x: x[2].dtype)

pandas/core/reshape/reshape.py

@@ -6,6 +6,7 @@
 import pandas._libs.algos as libalgos
 import pandas._libs.reshape as libreshape
 from pandas._libs.sparse import IntIndex
+from pandas._typing import Dtype
 from pandas.util._decorators import cache_readonly
 
 from pandas.core.dtypes.cast import maybe_promote
@@ -732,11 +733,11 @@ def get_dummies(
  data,
  prefix=None,
  prefix_sep="_",
- dummy_na=False,
+ dummy_na: bool = False,
  columns=None,
- sparse=False,
- drop_first=False,
- dtype=None,
+ sparse: bool = False,
+ drop_first: bool = False,
+ dtype: Optional[Dtype] = None,
 ) -> "DataFrame":
  """
  Convert categorical variable into dummy/indicator variables.
@@ -921,7 +922,7 @@ def _get_dummies_1d(
  dummy_na=False,
  sparse=False,
  drop_first=False,
- dtype=None,
+ dtype: Optional[Dtype] = None,
 ):
  from pandas.core.reshape.concat import concat
 

pandas/core/series.py

@@ -28,10 +28,12 @@
  AggFuncType,
  ArrayLike,
  Axis,
+ Dtype,
  DtypeObj,
  FrameOrSeriesUnion,
  IndexKeyFunc,
  Label,
+ NpDtype,
  StorageOptions,
  ValueKeyFunc,
 )
@@ -214,7 +216,13 @@ class Series(base.IndexOpsMixin, generic.NDFrame):
  # Constructors
 
  def __init__(
- self, data=None, index=None, dtype=None, name=None, copy=False, fastpath=False
+ self,
+ data=None,
+ index=None,
+ dtype: Optional[Dtype] = None,
+ name=None,
+ copy: bool = False,
+ fastpath: bool = False,
  ):
 
  if (
@@ -337,7 +345,7 @@ def __init__(
  self.name = name
  self._set_axis(0, index, fastpath=True)
 
- def _init_dict(self, data, index=None, dtype=None):
+ def _init_dict(self, data, index=None, dtype: Optional[Dtype] = None):
  """
  Derive the "_mgr" and "index" attributes of a new Series from a
  dictionary input.
@@ -612,7 +620,7 @@ def __len__(self) -> int:
  """
  return len(self._mgr)
 
- def view(self, dtype=None) -> "Series":
+ def view(self, dtype: Optional[Dtype] = None) -> "Series":
  """
  Create a new view of the Series.
 
@@ -686,7 +694,7 @@ def view(self, dtype=None) -> "Series":
  # NDArray Compat
  _HANDLED_TYPES = (Index, ExtensionArray, np.ndarray)
 
- def __array__(self, dtype=None) -> np.ndarray:
+ def __array__(self, dtype: Optional[NpDtype] = None) -> np.ndarray:
  """
  Return the values as a NumPy array.